RARA: Zero-shot Sim2Real Visual Navigation with Following Foreground Cues

Related tags

Deep Learningfgbg
Overview

RARA: Zero-shot Sim2Real Visual Navigation with Following Foreground Cues

FGBG (foreground-background) pytorch package for defining and training models. For a demo, please watch: https://youtu.be/nnnhLXBl8J8

Install Imitation-learning codebase for data collection and evaluation in simulation

See instruction here: https://github.com/kkelchte/imitation-learning-codebase. If the installation went fluently you should be able to create a dataset from within your sourced singularity environment:

python3.8 src/sim/ros/src/data_collection_fg_bg.py

This will create a json and hdf5 file of a number of flewn trajectories in the line world.

Install FGBG in a conda environment

conda create --yes --name venv python=3.6
conda activate venv
conda install --yes --file requirements-conda
conda install --yes pytorch torchvision cudatoolkit=11.0 -c pytorch 
python -m pip install -r requirements-pip

Train your models for extracting the foreground and background

Pretrain a model with bg augmentation from MITplaces stored in data/datasets/places

python run.py --config_file configs/deep_supervision_triplet.json --texture_directory data/datasets/places --target line --output_dir data/mymodel

Finetune the final layers for waypoint prediction with

python run.py --config_file configs/deep_supervision_triplet.json --texture_directory data/datasets/places --target line --encoder_ckpt_dir data/mymodel --output_dir data/mymodel/waypoints --task waypoints

Evaluate neural network on both simulated and real bebop drone

From within the singularity environment, you can run the following files. Make sure you adjust each file to the correct task (waypoints) and the correct checkpoint directory (data/mymodel/waypoints).

For evaluation in simulation:

python3.8 src/sim/ros/src/online_evaluation_fgbg.py

For evaluation on the real bebop drone, make sure you connect to the wifi of the drone before launching:

python3.8 src/sim/ros/src/online_evaluation_fgbg_real.py
rosrun imitation-learning-ros-package fgbg_actor.py

If everything goes according to plan, a console view should pop up with the life mask predictions as well as the waypoints. In order to start the autonomous flight, you can either use the keyboard or the joystick interface to publish an emtpy message on the '/go' topic. You can over take the experiments with publishing an empty message on the '/overtake' topic.

Troubleshoot

Just email me on kkelchtermans AT gmail.com. Thanks!

Owner
Klaas Kelchtermans
I was born as Klaas Kelchtermans
Klaas Kelchtermans
Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation

Uncertainty Estimation via Response Scaling for Pseudo-mask Noise Mitigation in Weakly-supervised Semantic Segmentation Introduction This is a PyTorch

XMed-Lab 30 Sep 23, 2022
내가 보려고 정리한 <프로그래밍 기초 Ⅰ> / organized for me

Programming-Basics 프로그래밍 기초 Ⅰ 아카이브 Do it! 점프 투 파이썬 주차 강의주제 비고 1주차 Syllabus 2주차 자료형 - 숫자형 3주차 자료형 - 문자열형 4주차 입력과 출력 5주차 제어문 - 조건문 if 6주차 제어문 - 반복문 whil

KIMMINSEO 1 Mar 07, 2022
High-resolution networks and Segmentation Transformer for Semantic Segmentation

High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v

HRNet 2.8k Jan 07, 2023
[CVPR'22] Official PyTorch Implementation of Collaborative Transformers for Grounded Situation Recognition

[CVPR'22] Collaborative Transformers for Grounded Situation Recognition Paper | Model Checkpoint This is the official PyTorch implementation of Collab

Junhyeong Cho 29 Dec 10, 2022
Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.

Smaller Multilingual Transformers This repository shares smaller versions of multilingual transformers that keep the same representations offered by t

Geotrend 79 Dec 28, 2022
Deep Inside Convolutional Networks - This is a caffe implementation to visualize the learnt model

Deep Inside Convolutional Networks This is a caffe implementation to visualize the learnt model. Part of a class project at Georgia Tech Problem State

Jigar 61 Apr 15, 2022
Official implementation of AAAI-21 paper "Label Confusion Learning to Enhance Text Classification Models"

Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str

101 Nov 25, 2022
Asymmetric metric learning for knowledge transfer

Asymmetric metric learning This is the official code that enables the reproduction of the results from our paper: Asymmetric metric learning for knowl

20 Dec 06, 2022
Unofficial keras(tensorflow) implementation of MAE model from Masked Autoencoders Are Scalable Vision Learners

MAE-keras Unofficial keras(tensorflow) implementation of MAE model described in 'Masked Autoencoders Are Scalable Vision Learners'. This work has been

Yewon 11 Jun 12, 2022
Generate Cartoon Images using Generative Adversarial Network

AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin

Aakash Jhawar 50 Dec 29, 2022
coldcuts is an R package to automatically generate and plot segmentation drawings in R

coldcuts coldcuts is an R package that allows you to draw and plot automatically segmentations from 3D voxel arrays. The name is inspired by one of It

2 Sep 03, 2022
A PyTorch library for Vision Transformers

VFormer A PyTorch library for Vision Transformers Getting Started Read the contributing guidelines in CONTRIBUTING.rst to learn how to start contribut

Society for Artificial Intelligence and Deep Learning 142 Nov 28, 2022
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering

[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt

Sai Kumar Dwivedi 83 Nov 27, 2022
Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel

Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel This repository is the official PyTorch implementation of BSRDM w

Zongsheng Yue 69 Jan 05, 2023
https://arxiv.org/abs/2102.11005

LogME LogME: Practical Assessment of Pre-trained Models for Transfer Learning How to use Just feed the features f and labels y to the function, and yo

THUML: Machine Learning Group @ THSS 149 Dec 19, 2022
Paper: Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification

Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification T M Feroz Ali, Subhasis Chaudhuri, ICVGIP-20-21

T M Feroz Ali 3 Jun 17, 2022
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

蒋子航 383 Dec 27, 2022
[ICCV 2021] Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

Amplitude-Phase Recombination (ICCV'21) Official PyTorch implementation of "Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neur

Guangyao Chen 53 Oct 05, 2022
Management Dashboard for Torchserve

Torchserve Dashboard Torchserve Dashboard using Streamlit Related blog post Usage Additional Requirement: torchserve (recommended:v0.5.2) Simply run:

Ceyda Cinarel 103 Dec 10, 2022
The codes and related files to reproduce the results for Image Similarity Challenge Track 2.

ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with

Wenhao Wang 89 Jan 02, 2023